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Mathematics & Statistics
New mathematics and statistics is posted on arXiv, often long before it appears in a journal. This page shows the newest papers ReadSearch has read, from algebra and geometry to analysis, probability and applied mathematics.
The newest 1,000 papers, from 13 October 2026 to 5 November 2026: 971 arXiv preprints and 29 OpenAlex records.
Newest papers, page 25
A New Formulation of the Elastica Model with Application to Image Inpainting
Curves and interfaces play a central role in computer vision and image processing, and Euler's elastica energy is one of the most successful tools to model and manipulate them.A proof of the Murty--Simon conjecture on diameter-$2$-critical graphs
The Murty-Simon conjecture states that every $n$-vertex diameter-$2$-critical graph has at most $\lfloor n^2/4 \rfloor$ edges, with equality only for the balanced complete bipartite graph.Radial power-like potentials: from the Bohr-Sommerfeld $\ell \neq 0$ state energies to the exact ones
Two new Bohr-Sommerfeld (B-S) type quantization conditions for $d$-dimensional radial potentials are proposed for non-singular and singular potentials, respectively.A Simple Presentation of Robust Membership Inference Attacks
In a membership inference attack, an attacker is given the data of a particular individual, and tries to determine if that individual was included in a particular dataset, given some kind of…Underdamped Anchored Langevin Dynamics
Classical Langevin Monte Carlo algorithms, such as the unadjusted Langevin algorithm (ULA), are based on discretization schemes of the overdamped Langevin dynamics and are widely used for sampling…Risk measures for infinite-server queues driven by a Cox-BESQ process
This paper introduces a model for infinite-server queues driven by a Cox process with stochastic intensity given by a squared Bessel (BESQ) process.Second-order Sinkhorn Geometry and $\sqrt{n}$-Inference
The Sinkhorn divergence, a debiased form of entropic optimal transport, has been widely used in various scientific disciplines due to its computational and statistical tractability.NextEval: An Agent-Based Solver and Benchmark for Derivative-Free Optimization
Derivative-free optimization (DFO) addresses problems where derivatives are unavailable or costly to obtain.QESChunker: A Single Objective Unifies Overlapping and Non-Overlapping Chunking for RAG
Chunking is a fundamental preprocessing step in retrieval-augmented generation (RAG), yet most existing chunkers rely primarily on heuristics.Holomorphic Cauchy Networks for Efficient Stationary Tail Computation in High-Dimensional Reflected Brownian Motions
Stationary tail computation for high-dimensional reflected Brownian motions (RBMs) remains computationally challenging.Wasserstein approximation of measures via orthogonal frames: statistical and computational complexities
Dimension-reduction methods such as PCA identify a subspace capturing most of the variation in the data, but not a distinguished basis within it.Balanced State Subspaces for Mamba-2 State Compression
Mamba-2 compresses all context into a fixed-size recurrent state that dominates decoding memory and bandwidth.The uneven rise of AI-generated web content
In less than five years, generative artificial intelligence (AI) has dramatically reshaped the public-facing web.Generative Refinement Learning for Temporal Interpolation in Scientific Machine Learning
Computationally expensive simulations and real-world observations often provide data at a lower temporal resolution than downstream tasks require.Frequency-Uniform Log-Regret Reinforcement Learning for Diffusions
High-frequency control problems are often studied through time discretization, but refining the timestep $δ$ increases the discrete horizon $H=T/δ$ and can make standard finite-horizon regret…LLM knowledge for improved Out-of-Distribution Tabular Prediction - A Cross-Validated Regularisation Approach
Prediction models degrade when the deployment population differs from the one used to train them, and training data cannot say which feature-response relationships will transfer.Joint Distributional Copula Regression for Insurance Claim Frequency and Severity via Boosting
In this paper, we introduce a model-based boosting approach for fitting structured additive distributional copula regression models for bivariate responses, with particular emphasis on jointly…Boundary Geometry Determines Optimal Shallow ReLU Approximation under Weighted Coefficient Constraints
We study how boundary geometry affects $L^q$ approximation by shallow ReLU neural networks on convex bodies $K\subset\mathbb R^d$.RePAIR: Inverting Backdoor Attacks in Semantic Segmentation
Despite significant advances in computer vision, semantic segmentation models remain vulnerable to backdoor attacks, posing a security risk.Is Your LLM Relay Serving What It Claims? A low-cost and high-power test for LLM Relay Auditing
Relay and reseller APIs have become a common way to access large language models (LLMs), yet users cannot directly verify whether they receive the models they request and pay for.
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